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1. A framework for detecting noncoding rare-variant associations of large-scale whole-genome sequencing studies

Author

Li, Zilin, Li, Xihao, Zhou, Hufeng, Gaynor, Sheila M., Selvaraj, Margaret Sunitha, Arapoglou, Theodore, Quick, Corbin, Liu, Yaowu, Chen, Han, Sun, Ryan, Dey, Rounak, Arnett, Donna K., Auer, Paul L., Bielak, Lawrence F., Bis, Joshua C., Blackwell, Thomas W., Blangero, John, Boerwinkle, Eric, Bowden, Donald W., Brody, Jennifer A., Cade, Brian E., Conomos, Matthew P., Correa, Adolfo, Cupples, L. Adrienne, Curran, Joanne E., de Vries, Paul S., Duggirala, Ravindranath, Franceschini, Nora, Freedman, Barry I., Göring, Harald H. H., Guo, Xiuqing, Kalyani, Rita R., Kooperberg, Charles, Kral, Brian G., Lange, Leslie A., Lin, Bridget M., Manichaikul, Ani, Manning, Alisa K., Martin, Lisa W., Mathias, Rasika A., Meigs, James B., Mitchell, Braxton D., Montasser, May E., Morrison, Alanna C., Naseri, Take, O’Connell, Jeffrey R., Palmer, Nicholette D., Peyser, Patricia A., Psaty, Bruce M., Raffield, Laura M., Redline, Susan, Reiner, Alexander P., Reupena, Muagututi‘a Sefuiva, Rice, Kenneth M., Rich, Stephen S., Smith, Jennifer A., Taylor, Kent D., Taub, Margaret A., Vasan, Ramachandran S., Weeks, Daniel E., Wilson, James G., Yanek, Lisa R., Zhao, Wei, Rotter, Jerome I., Willer, Cristen J., Natarajan, Pradeep, Peloso, Gina M., and Lin, Xihong

Subjects
Genome, Phenotype, Whole Genome Sequencing, Humans, Genetic Variation, Cell Biology, Polymorphism, Single Nucleotide, Molecular Biology, Biochemistry, Article, Biological Specimen Banks, Genome-Wide Association Study, Biotechnology
Abstract

Large-scale whole-genome sequencing studies have enabled analysis of noncoding rare-variant (RV) associations with complex human diseases and traits. Variant-set analysis is a powerful approach to study RV association. However, existing methods have limited ability in analyzing the noncoding genome. We propose a computationally efficient and robust noncoding RV association detection framework, STAARpipeline, to automatically annotate a whole-genome sequencing study and perform flexible noncoding RV association analysis, including gene-centric analysis and fixed window-based and dynamic window-based non-gene-centric analysis by incorporating variant functional annotations. In gene-centric analysis, STAARpipeline uses STAAR to group noncoding variants based on functional categories of genes and incorporate multiple functional annotations. In non-gene-centric analysis, STAARpipeline uses SCANG-STAAR to incorporate dynamic window sizes and multiple functional annotations. We apply STAARpipeline to identify noncoding RV sets associated with four lipid traits in 21,015 discovery samples from the Trans-Omics for Precision Medicine (TOPMed) program and replicate several of them in an additional 9,123 TOPMed samples. We also analyze five non-lipid TOPMed traits.

Published
2022
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2. The genetic determinants of recurrent somatic mutations in 43,693 blood genomes

Author

Weinstock, Joshua S, Laurie, Cecelia A, Broome, Jai G, Taylor, Kent D, Guo, Xiuqing, Shuldiner, Alan R, O'Connell, Jeffrey R, Lewis, Joshua P, Boerwinkle, Eric, Barnes, Kathleen C, Chami, Nathalie, Kenny, Eimear E, Loos, Ruth JF, Fornage, Myriam, Redline, Susan, Cade, Brian E, Gilliland, Frank D, Chen, Zhanghua, Gauderman, W James, Kumar, Rajesh, Grammer, Leslie, Schleimer, Robert P, Psaty, Bruce M, Bis, Joshua C, Brody, Jennifer A, Silverman, Edwin K, Yun, Jeong H, Qiao, Dandi, Weiss, Scott T, Lasky-Su, Jessica, DeMeo, Dawn L, Palmer, Nicholette D, Freedman, Barry I, Bowden, Donald W, Cho, Michael H, Vasan, Ramachandran S, Johnson, Andrew D, Yanek, Lisa R, Becker, Lewis C, Kardia, Sharon, He, Jiang, Kaplan, Robert, Heckbert, Susan R, Smith, Nicholas L, Wiggins, Kerri L, Arnett, Donna K, Irvin, Marguerite R, Tiwari, Hemant, Correa, Adolfo, Raffield, Laura M, Gao, Yan, de Andrade, Mariza, Rotter, Jerome I, Rich, Stephen S, Manichaikul, Ani W, Konkle, Barbara A, Johnsen, Jill M, Wheeler, Marsha M, Custer, Brian S, Duggirala, Ravindranath, Curran, Joanne E, Blangero, John, Gui, Hongsheng, Xiao, Shujie, Williams, L Keoki, Meyers, Deborah A, Li, Xingnan, Ortega, Victor, McGarvey, Stephen, Gu, C Charles, Chen, Yii-Der Ida, Lee, Wen-Jane, Shoemaker, M Benjamin, Darbar, Dawood, Roden, Dan, Albert, Christine, Kooperberg, Charles, Desai, Pinkal, Blackwell, Thomas W, Abecasis, Goncalo R, Smith, Albert V, Kang, Hyun M, Mathias, Rasika, Natarajan, Pradeep, Jaiswal, Siddhartha, Reiner, Alexander P, Bick, Alexander G, and NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium

Subjects
Human Genome, Middle Aged, Hematopoiesis, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, Phenotype, Good Health and Well Being, Clinical Research, Mutation, Genetics, Humans, 2.1 Biological and endogenous factors, Genetic Testing, Missense, Aetiology, Lung, Germ-Line Mutation, Biotechnology
Abstract

Nononcogenic somatic mutations are thought to be uncommon and inconsequential. To test this, we analyzed 43,693 National Heart, Lung and Blood Institute Trans-Omics for Precision Medicine blood whole genomes from 37 cohorts and identified 7131 non-missense somatic mutations that are recurrently mutated in at least 50 individuals. These recurrent non-missense somatic mutations (RNMSMs) are not clearly explained by other clonal phenomena such as clonal hematopoiesis. RNMSM prevalence increased with age, with an average 50-year-old having 27 RNMSMs. Inherited germline variation associated with RNMSM acquisition. These variants were found in genes involved in adaptive immune function, proinflammatory cytokine production, and lymphoid lineage commitment. In addition, the presence of eight specific RNMSMs associated with blood cell traits at effect sizes comparable to Mendelian genetic mutations. Overall, we found that somatic mutations in blood are an unexpectedly common phenomenon with ancestry-specific determinants and human health consequences.

Published
2023

3. TOP-LD: A tool to explore linkage disequilibrium with TOPMed whole-genome sequence data

Author

Huang, Le, Rosen, Jonathan D, Sun, Quan, Chen, Jiawen, Wheeler, Marsha M, Zhou, Ying, Min, Yuan-I, Kooperberg, Charles, Conomos, Matthew P, Stilp, Adrienne M, Rich, Stephen S, Rotter, Jerome I, Manichaikul, Ani, Loos, Ruth JF, Kenny, Eimear E, Blackwell, Thomas W, Smith, Albert V, Jun, Goo, Sedlazeck, Fritz J, Metcalf, Ginger, Boerwinkle, Eric, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, Raffield, Laura M, Reiner, Alex P, Auer, Paul L, and Li, Yun

Subjects
Genetics & Heredity, Whole Genome Sequencing, Human Genome, Single Nucleotide, Biological Sciences, Medical and Health Sciences, Linkage Disequilibrium, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, Good Health and Well Being, Asian People, Genetics, Humans, Polymorphism, Precision Medicine, Genome-Wide Association Study, Biotechnology
Abstract

Current publicly available tools that allow rapid exploration of linkage disequilibrium (LD) between markers (e.g., HaploReg and LDlink) are based on whole-genome sequence (WGS) data from 2,504 individuals in the 1000 Genomes Project. Here, we present TOP-LD, an online tool to explore LD inferred with high-coverage (∼30×) WGS data from 15,578 individuals in the NHLBI Trans-Omics for Precision Medicine (TOPMed) program. TOP-LD provides a significant upgrade compared to current LD tools, as the TOPMed WGS data provide a more comprehensive representation of genetic variation than the 1000 Genomes data, particularly for rare variants and in the specific populations that we analyzed. For example, TOP-LD encompasses LD information for 150.3, 62.2, and 36.7 million variants for European, African, and East Asian ancestral samples, respectively, offering 2.6- to 9.1-fold increase in variant coverage compared to HaploReg 4.0 or LDlink. In addition, TOP-LD includes tens of thousands of structural variants (SVs). We demonstrate the value of TOP-LD in fine-mapping at the GGT1 locus associated with gamma glutamyltransferase in the African ancestry participants in UK Biobank. Beyond fine-mapping, TOP-LD can facilitate a wide range of applications that are based on summary statistics and estimates of LD. TOP-LD is freely available online.

Published
2022

4. Mendelian randomization supports bidirectional causality between telomere length and clonal hematopoiesis of indeterminate potential

Author

Nakao, Tetsushi, Bick, Alexander G, Taub, Margaret A, Zekavat, Seyedeh M, Uddin, Md M, Niroula, Abhishek, Carty, Cara L, Lane, John, Honigberg, Michael C, Weinstock, Joshua S, Pampana, Akhil, Gibson, Christopher J, Griffin, Gabriel K, Clarke, Shoa L, Bhattacharya, Romit, Assimes, Themistocles L, Emery, Leslie S, Stilp, Adrienne M, Wong, Quenna, Broome, Jai, Laurie, Cecelia A, Khan, Alyna T, Smith, Albert V, Blackwell, Thomas W, Codd, Veryan, Nelson, Christopher P, Yoneda, Zachary T, Peralta, Juan M, Bowden, Donald W, Irvin, Marguerite R, Boorgula, Meher, Zhao, Wei, Yanek, Lisa R, Wiggins, Kerri L, Hixson, James E, Gu, C Charles, Peloso, Gina M, Roden, Dan M, Reupena, Muagututi'a S, Hwu, Chii-Min, DeMeo, Dawn L, North, Kari E, Kelly, Shannon, Musani, Solomon K, Bis, Joshua C, Lloyd-Jones, Donald M, Johnsen, Jill M, Preuss, Michael, Tracy, Russell P, Peyser, Patricia A, Qiao, Dandi, Desai, Pinkal, Curran, Joanne E, Freedman, Barry I, Tiwari, Hemant K, Chavan, Sameer, Smith, Jennifer A, Smith, Nicholas L, Kelly, Tanika N, Hidalgo, Bertha, Cupples, L Adrienne, Weeks, Daniel E, Hawley, Nicola L, Minster, Ryan L, Samoan Obesity, Lifestyle And Genetic Adaptations Study (OLaGA) Group, Deka, Ranjan, Naseri, Take T, De Las Fuentes, Lisa, Raffield, Laura M, Morrison, Alanna C, Vries, Paul S, Ballantyne, Christie M, Kenny, Eimear E, Rich, Stephen S, Whitsel, Eric A, Cho, Michael H, Shoemaker, M Benjamin, Pace, Betty S, Blangero, John, Palmer, Nicholette D, Mitchell, Braxton D, Shuldiner, Alan R, Barnes, Kathleen C, Redline, Susan, Kardia, Sharon LR, Abecasis, Gonçalo R, Becker, Lewis C, Heckbert, Susan R, He, Jiang, Post, Wendy, Arnett, Donna K, Vasan, Ramachandran S, Darbar, Dawood, Weiss, Scott T, McGarvey, Stephen T, De Andrade, Mariza, Chen, Yii-Der Ida, Kaplan, Robert C, Meyers, Deborah A, Custer, Brian S, Correa, Adolfo, Psaty, Bruce M, Fornage, Myriam, Manson, JoAnn E, Boerwinkle, Eric, Konkle, Barbara A, Loos, Ruth JF, Rotter, Jerome I, Silverman, Edwin K, Kooperberg, Charles, Danesh, John, Samani, Nilesh J, Jaiswal, Siddhartha, Libby, Peter, Ellinor, Patrick T, Pankratz, Nathan, Ebert, Benjamin L, Reiner, Alexander P, Mathias, Rasika A, Do, Ron, NHLBI Trans-Omics For Precision Medicine (TOPMed) Consortium, Natarajan, Pradeep, Nakao, Tetsushi [0000-0001-9979-2682], Bick, Alexander G [0000-0001-5824-9595], Zekavat, Seyedeh M [0000-0003-4026-8944], Uddin, Md M [0000-0003-1846-0411], Niroula, Abhishek [0000-0002-5904-0635], Carty, Cara L [0000-0002-6378-8195], Lane, John [0000-0002-3582-5825], Honigberg, Michael C [0000-0001-8630-5021], Weinstock, Joshua S [0000-0001-7013-1899], Pampana, Akhil [0000-0002-4167-0540], Griffin, Gabriel K [0000-0002-4042-6757], Clarke, Shoa L [0000-0002-6592-1172], Bhattacharya, Romit [0000-0002-0782-4753], Assimes, Themistocles L [0000-0003-2349-0009], Emery, Leslie S [0000-0002-9070-9886], Stilp, Adrienne M [0000-0002-3910-0776], Wong, Quenna [0000-0002-9027-2100], Broome, Jai [0000-0001-7638-0749], Khan, Alyna T [0000-0002-2240-7931], Smith, Albert V [0000-0003-1942-5845], Codd, Veryan [0000-0002-9430-8254], Nelson, Christopher P [0000-0001-8025-2897], Yoneda, Zachary T [0000-0002-2055-732X], Peralta, Juan M [0000-0002-8811-5579], Yanek, Lisa R [0000-0001-7117-1075], Wiggins, Kerri L [0000-0003-2749-1279], Gu, C Charles [0000-0002-8527-8145], Peloso, Gina M [0000-0002-5355-8636], Roden, Dan M [0000-0002-6302-0389], Hwu, Chii-Min [0000-0002-8209-9627], North, Kari E [0000-0002-8903-0366], Bis, Joshua C [0000-0002-3409-1110], Lloyd-Jones, Donald M [0000-0003-0847-6110], Johnsen, Jill M [0000-0002-2279-2550], Preuss, Michael [0000-0001-5266-8465], Tracy, Russell P [0000-0002-0080-2420], Peyser, Patricia A [0000-0002-9717-8459], Qiao, Dandi [0000-0001-9450-205X], Curran, Joanne E [0000-0002-6898-155X], Freedman, Barry I [0000-0003-0275-5530], Chavan, Sameer [0000-0002-0220-0845], Smith, Jennifer A [0000-0002-3575-5468], Kelly, Tanika N [0000-0002-7348-4451], Hidalgo, Bertha [0000-0002-2556-1969], Weeks, Daniel E [0000-0001-9410-7228], Hawley, Nicola L [0000-0002-2601-3454], Minster, Ryan L [0000-0001-7382-6717], de Las Fuentes, Lisa [0000-0002-4689-325X], Raffield, Laura M [0000-0002-7892-193X], Ballantyne, Christie M [0000-0002-6432-1730], Kenny, Eimear E [0000-0001-9198-759X], Rich, Stephen S [0000-0003-3872-7793], Whitsel, Eric A [0000-0003-4843-3641], Cho, Michael H [0000-0002-4907-1657], Palmer, Nicholette D [0000-0001-8883-2511], Mitchell, Braxton D [0000-0003-4920-4744], Shuldiner, Alan R [0000-0001-9921-4305], Redline, Susan [0000-0002-6585-1610], Heckbert, Susan R [0000-0002-7100-512X], He, Jiang [0000-0002-8286-9652], Post, Wendy [0000-0002-8655-5204], Arnett, Donna K [0000-0003-2219-657X], Vasan, Ramachandran S [0000-0001-7357-5970], Weiss, Scott T [0000-0001-7196-303X], McGarvey, Stephen T [0000-0003-1233-6970], Custer, Brian S [0000-0001-6251-366X], Correa, Adolfo [0000-0002-9501-600X], Manson, JoAnn E [0000-0002-9426-7595], Konkle, Barbara A [0000-0002-3959-8797], Loos, Ruth JF [0000-0002-8532-5087], Rotter, Jerome I [0000-0001-7191-1723], Silverman, Edwin K [0000-0002-3641-3822], Kooperberg, Charles [0000-0002-7986-8560], Samani, Nilesh J [0000-0002-3286-8133], Jaiswal, Siddhartha [0000-0002-9597-0477], Libby, Peter [0000-0002-1502-502X], Ellinor, Patrick T [0000-0002-2067-0533], Pankratz, Nathan [0000-0001-5958-693X], Ebert, Benjamin L [0000-0003-0197-5451], Mathias, Rasika A [0000-0002-2282-9042], Do, Ron [0000-0002-3144-3627], Natarajan, Pradeep [0000-0001-8402-7435], Apollo - University of Cambridge Repository, and Danesh, John [0000-0003-1158-6791]

Subjects
NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, Samoan Obesity, Lifestyle and Genetic Adaptations Study (OLaGA) Group
Abstract

Human genetic studies support an inverse causal relationship between leukocyte telomere length (LTL) and coronary artery disease (CAD), but directionally mixed effects for LTL and diverse malignancies. Clonal hematopoiesis of indeterminate potential (CHIP), characterized by expansion of hematopoietic cells bearing leukemogenic mutations, predisposes both hematologic malignancy and CAD. TERT (which encodes telomerase reverse transcriptase) is the most significantly associated germline locus for CHIP in genome-wide association studies. Here, we investigated the relationship between CHIP, LTL, and CAD in the Trans-Omics for Precision Medicine (TOPMed) program (n = 63,302) and UK Biobank (n = 47,080). Bidirectional Mendelian randomization studies were consistent with longer genetically imputed LTL increasing propensity to develop CHIP, but CHIP then, in turn, hastens to shorten measured LTL (mLTL). We also demonstrated evidence of modest mediation between CHIP and CAD by mLTL. Our data promote an understanding of potential causal relationships across CHIP and LTL toward prevention of CAD.

Published
2022
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5. Monogenic and Polygenic Contributions to QTc Prolongation in the Population

Author

Nauffal, Victor, Morrill, Valerie N, Jurgens, Sean J, Choi, Seung Hoan, Hall, Amelia W, Weng, Lu-Chen, Halford, Jennifer L, Austin-Tse, Christina, Haggerty, Christopher M, Harris, Stephanie L, Wong, Eugene K, Alonso, Alvaro, Arking, Dan E, Benjamin, Emelia J, Boerwinkle, Eric, Min, Yuan-I, Correa, Adolfo, Fornwalt, Brandon K, Heckbert, Susan R, National Heart, Lung, and Blood Institute Trans-Omics for Precision Medicine (TOPMed) Consortium, Kooperberg, Charles, Lin, Henry J, J F Loos, Ruth, Rice, Kenneth M, Gupta, Namrata, Blackwell, Thomas W, Mitchell, Braxton D, Morrison, Alanna C, Psaty, Bruce M, Post, Wendy S, Redline, Susan, Rehm, Heidi L, Rich, Stephen S, Rotter, Jerome I, Soliman, Elsayed Z, Sotoodehnia, Nona, Lunetta, Kathryn L, Ellinor, Patrick T, Lubitz, Steven A, and TOPMed Investigators

Subjects
QT interval, Heterozygote, Multifactorial Inheritance, TOPMed Investigators, Clinical Sciences, polygenic, Cardiorespiratory Medicine and Haematology, Cardiovascular, sudden cardiac death, Electrocardiography, and Blood Institute Trans-Omics for Precision Medicine (TOPMed) Consortium, monogenic, long QT syndrome, Genetics, Humans, 2.1 Biological and endogenous factors, Aetiology, Lung, Whole Genome Sequencing, Prevention, Human Genome, National Heart, Long QT Syndrome, Heart Disease, Good Health and Well Being, Cardiovascular System & Hematology, Public Health and Health Services, Genome-Wide Association Study
Abstract

BackgroundRare sequence variation in genes underlying cardiac repolarization and common polygenic variation influence QT interval duration. However, current clinical genetic testing of individuals with unexplained QT prolongation is restricted to examination of monogenic rare variants. The recent emergence of large-scale biorepositories with sequence data enables examination of the joint contribution of rare and common variations to the QT interval in the population.MethodsWe performed a genome-wide association study of the QTc in 84 630 UK Biobank participants and created a polygenic risk score (PRS). Among 26 976 participants with whole-genome sequencing and ECG data in the TOPMed (Trans-Omics for Precision Medicine) program, we identified 160 carriers of putative pathogenic rare variants in 10 genes known to be associated with the QT interval. We examined QTc associations with the PRS and with rare variants in TOPMed.ResultsFifty-four independent loci were identified by genome-wide association study in the UK Biobank. Twenty-one loci were novel, of which 12 were replicated in TOPMed. The PRS composed of 1 110 494 common variants was significantly associated with the QTc in TOPMed (ΔQTc/decile of PRS=1.4 ms [95% CI, 1.3 to 1.5]; P=1.1×10-196). Carriers of putative pathogenic rare variants had longer QTc than noncarriers (ΔQTc=10.9 ms [95% CI, 7.4 to 14.4]). Of individuals with QTc>480 ms, 23.7% carried either a monogenic rare variant or had a PRS in the top decile (3.4% monogenic, 21% top decile of PRS).ConclusionsQTc duration in the population is influenced by both rare variants in genes underlying cardiac repolarization and polygenic risk, with a sizeable contribution from polygenic risk. Comprehensive assessment of the genetic determinants of QTc prolongation includes incorporation of both polygenic and monogenic risk.

Published
2022

6. Mendelian randomization supports bidirectional causality between telomere length and clonal hematopoiesis of indeterminate potential

Author

Nakao, Tetsushi, Bick, Alexander G, Taub, Margaret A, Zekavat, Seyedeh M, Uddin, Md M, Niroula, Abhishek, Carty, Cara L, Lane, John, Honigberg, Michael C, Weinstock, Joshua S, Pampana, Akhil, Gibson, Christopher J, Griffin, Gabriel K, Clarke, Shoa L, Bhattacharya, Romit, Assimes, Themistocles L, Emery, Leslie S, Stilp, Adrienne M, Wong, Quenna, Broome, Jai, Laurie, Cecelia A, Khan, Alyna T, Smith, Albert V, Blackwell, Thomas W, Codd, Veryan, Nelson, Christopher P, Yoneda, Zachary T, Peralta, Juan M, Bowden, Donald W, Irvin, Marguerite R, Boorgula, Meher, Zhao, Wei, Yanek, Lisa R, Wiggins, Kerri L, Hixson, James E, Gu, C Charles, Peloso, Gina M, Roden, Dan M, Reupena, Muagututi'a S, Hwu, Chii-Min, DeMeo, Dawn L, North, Kari E, Kelly, Shannon, Musani, Solomon K, Bis, Joshua C, Lloyd-Jones, Donald M, Johnsen, Jill M, Preuss, Michael, Tracy, Russell P, Peyser, Patricia A, Qiao, Dandi, Desai, Pinkal, Curran, Joanne E, Freedman, Barry I, Tiwari, Hemant K, Chavan, Sameer, Smith, Jennifer A, Smith, Nicholas L, Kelly, Tanika N, Hidalgo, Bertha, Cupples, L Adrienne, Weeks, Daniel E, Hawley, Nicola L, Minster, Ryan L, Samoan Obesity, Lifestyle and Genetic Adaptations Study (OLaGA) Group, Deka, Ranjan, Naseri, Take T, de Las Fuentes, Lisa, Raffield, Laura M, Morrison, Alanna C, Vries, Paul S, Ballantyne, Christie M, Kenny, Eimear E, Rich, Stephen S, Whitsel, Eric A, Cho, Michael H, Shoemaker, M Benjamin, Pace, Betty S, Blangero, John, Palmer, Nicholette D, Mitchell, Braxton D, Shuldiner, Alan R, Barnes, Kathleen C, Redline, Susan, Kardia, Sharon LR, Abecasis, Gonçalo R, Becker, Lewis C, Heckbert, Susan R, He, Jiang, Post, Wendy, Arnett, Donna K, Vasan, Ramachandran S, Darbar, Dawood, Weiss, Scott T, McGarvey, Stephen T, de Andrade, Mariza, Chen, Yii-Der Ida, Kaplan, Robert C, Meyers, Deborah A, and Custer, Brian S

Subjects
Lifestyle and Genetic Adaptations Study (OLaGA) Group, Aging, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, Heart Disease, Human Genome, Genetics, 2.1 Biological and endogenous factors, Samoan Obesity, Atherosclerosis, Cardiovascular, Heart Disease - Coronary Heart Disease
Abstract

Human genetic studies support an inverse causal relationship between leukocyte telomere length (LTL) and coronary artery disease (CAD), but directionally mixed effects for LTL and diverse malignancies. Clonal hematopoiesis of indeterminate potential (CHIP), characterized by expansion of hematopoietic cells bearing leukemogenic mutations, predisposes both hematologic malignancy and CAD. TERT (which encodes telomerase reverse transcriptase) is the most significantly associated germline locus for CHIP in genome-wide association studies. Here, we investigated the relationship between CHIP, LTL, and CAD in the Trans-Omics for Precision Medicine (TOPMed) program (n = 63,302) and UK Biobank (n = 47,080). Bidirectional Mendelian randomization studies were consistent with longer genetically imputed LTL increasing propensity to develop CHIP, but CHIP then, in turn, hastens to shorten measured LTL (mLTL). We also demonstrated evidence of modest mediation between CHIP and CAD by mLTL. Our data promote an understanding of potential causal relationships across CHIP and LTL toward prevention of CAD.

Published
2022

7. Whole-genome sequencing in diverse subjects identifies genetic correlates of leukocyte traits: The NHLBI TOPMed program

Author

Mikhaylova, Anna V, McHugh, Caitlin P, Polfus, Linda M, Raffield, Laura M, Boorgula, Meher Preethi, Blackwell, Thomas W, Brody, Jennifer A, Broome, Jai, Chami, Nathalie, Chen, Ming-Huei, Conomos, Matthew P, Cox, Corey, Curran, Joanne E, Daya, Michelle, Ekunwe, Lynette, Glahn, David C, Heard-Costa, Nancy, Highland, Heather M, Hobbs, Brian D, Ilboudo, Yann, Jain, Deepti, Lange, Leslie A, Miller-Fleming, Tyne W, Min, Nancy, Moon, Jee-Young, Preuss, Michael H, Rosen, Jonathon, Ryan, Kathleen, Smith, Albert V, Sun, Quan, Surendran, Praveen, de Vries, Paul S, Walter, Klaudia, Wang, Zhe, Wheeler, Marsha, Yanek, Lisa R, Zhong, Xue, Abecasis, Goncalo R, Almasy, Laura, Barnes, Kathleen C, Beaty, Terri H, Becker, Lewis C, Blangero, John, Boerwinkle, Eric, Butterworth, Adam S, Chavan, Sameer, Cho, Michael H, Choquet, Hélène, Correa, Adolfo, Cox, Nancy, DeMeo, Dawn L, Faraday, Nauder, Fornage, Myriam, Gerszten, Robert E, Hou, Lifang, Johnson, Andrew D, Jorgenson, Eric, Kaplan, Robert, Kooperberg, Charles, Kundu, Kousik, Laurie, Cecelia A, Lettre, Guillaume, Lewis, Joshua P, Li, Bingshan, Li, Yun, Lloyd-Jones, Donald M, Loos, Ruth JF, Manichaikul, Ani, Meyers, Deborah A, Mitchell, Braxton D, Morrison, Alanna C, Ngo, Debby, Nickerson, Deborah A, Nongmaithem, Suraj, North, Kari E, O'Connell, Jeffrey R, Ortega, Victor E, Pankratz, Nathan, Perry, James A, Psaty, Bruce M, Rich, Stephen S, Soranzo, Nicole, Rotter, Jerome I, Silverman, Edwin K, Smith, Nicholas L, Tang, Hua, Tracy, Russell P, Thornton, Timothy A, Vasan, Ramachandran S, Zein, Joe, Mathias, Rasika A, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, Reiner, Alexander P, and Auer, Paul L

Subjects
Chronic Obstructive, Proteome, Quantitative Trait Loci, Dermatitis, Medical and Health Sciences, Atopic, blood-cell counts, Pulmonary Disease, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, and Blood Institute (U.S.), Leukocytes, Genetics, Humans, 2.1 Biological and endogenous factors, Genetic Predisposition to Disease, Polymorphism, Aetiology, Lung, Genetics & Heredity, Genome, Whole Genome Sequencing, Inflammatory and immune system, Human Genome, Single Nucleotide, National Heart, Biological Sciences, Prognosis, Asthma, United States, United Kingdom, Phenotype, Good Health and Well Being, whole-genome sequencing, Biomarkers, Human, Genome-Wide Association Study
Abstract

Many common and rare variants associated with hematologic traits have been discovered through imputation on large-scale reference panels. However, the majority of genome-wide association studies (GWASs) have been conducted in Europeans, and determining causal variants has proved challenging. We performed a GWAS of total leukocyte, neutrophil, lymphocyte, monocyte, eosinophil, and basophil counts generated from 109,563,748 variants in the autosomes and the X chromosome in the Trans-Omics for Precision Medicine (TOPMed) program, which included data from 61,802 individuals of diverse ancestry. We discovered and replicated 7 leukocyte trait associations, including (1) the association between a chromosome X, pseudo-autosomal region (PAR), noncoding variant located between cytokine receptor genes (CSF2RA and CLRF2) and lower eosinophil count; and (2) associations between single variants found predominantly among African Americans at the S1PR3 (9q22.1) and HBB (11p15.4) loci and monocyte and lymphocyte counts, respectively. We further provide evidence indicating that the newly discovered eosinophil-lowering chromosome X PAR variant might be associated with reduced susceptibility to common allergic diseases such as atopic dermatitis and asthma. Additionally, we found a burden of very rare FLT3 (13q12.2) variants associated with monocyte counts. Together, these results emphasize the utility of whole-genome sequencing in diverse samples in identifying associations missed by European-ancestry-driven GWASs.

Published
2021

8. Association of mitochondrial DNA copy number with cardiometabolic diseases

Author

Liu, Xue, Longchamps, Ryan J, Wiggins, Kerri L, Raffield, Laura M, Bielak, Lawrence F, Zhao, Wei, Pitsillides, Achilleas, Blackwell, Thomas W, Yao, Jie, Guo, Xiuqing, Kurniansyah, Nuzulul, Thyagarajan, Bharat, Pankratz, Nathan, Rich, Stephen S, Taylor, Kent D, Peyser, Patricia A, Heckbert, Susan R, Seshadri, Sudha, Cupples, L Adrienne, Boerwinkle, Eric, Grove, Megan L, Larson, Nicholas B, Smith, Jennifer A, Vasan, Ramachandran S, Sofer, Tamar, Fitzpatrick, Annette L, Fornage, Myriam, Ding, Jun, Correa, Adolfo, Abecasis, Goncalo, Psaty, Bruce M, Wilson, James G, Levy, Daniel, Rotter, Jerome I, Bis, Joshua C, TOPMed mtDNA Working Group in NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, Satizabal, Claudia L, Arking, Dan E, and Liu, Chunyu

Subjects
Aging, Good Health and Well Being, TOPMed mtDNA Working Group in NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, Genetics, Generic health relevance, Metabolic and endocrine
Abstract

Mitochondrial DNA (mtDNA) is present in multiple copies in human cells. We evaluated cross-sectional associations of whole blood mtDNA copy number (CN) with several cardiometabolic disease traits in 408,361 participants of multiple ancestries in TOPMed and UK Biobank. Age showed a threshold association with mtDNA CN: among younger participants (

Published
2021

9. Whole-genome sequencing association analysis of quantitative red blood cell phenotypes: The NHLBI TOPMed program

Author

Hu, Yao, Stilp, Adrienne M, McHugh, Caitlin P, Rao, Shuquan, Jain, Deepti, Zheng, Xiuwen, Lane, John, Méric de Bellefon, Sébastian, Raffield, Laura M, Chen, Ming-Huei, Yanek, Lisa R, Wheeler, Marsha, Yao, Yao, Ren, Chunyan, Broome, Jai, Moon, Jee-Young, de Vries, Paul S, Hobbs, Brian D, Sun, Quan, Surendran, Praveen, Brody, Jennifer A, Blackwell, Thomas W, Choquet, Hélène, Ryan, Kathleen, Duggirala, Ravindranath, Heard-Costa, Nancy, Wang, Zhe, Chami, Nathalie, Preuss, Michael H, Min, Nancy, Ekunwe, Lynette, Lange, Leslie A, Cushman, Mary, Faraday, Nauder, Curran, Joanne E, Almasy, Laura, Kundu, Kousik, Smith, Albert V, Gabriel, Stacey, Rotter, Jerome I, Fornage, Myriam, Lloyd-Jones, Donald M, Vasan, Ramachandran S, Smith, Nicholas L, North, Kari E, Boerwinkle, Eric, Becker, Lewis C, Lewis, Joshua P, Abecasis, Goncalo R, Hou, Lifang, O'Connell, Jeffrey R, Morrison, Alanna C, Beaty, Terri H, Kaplan, Robert, Correa, Adolfo, Blangero, John, Jorgenson, Eric, Psaty, Bruce M, Kooperberg, Charles, Walton, Russell T, Kleinstiver, Benjamin P, Tang, Hua, Loos, Ruth JF, Soranzo, Nicole, Butterworth, Adam S, Nickerson, Debbie, Rich, Stephen S, Mitchell, Braxton D, Johnson, Andrew D, Auer, Paul L, Li, Yun, Mathias, Rasika A, Lettre, Guillaume, Pankratz, Nathan, Laurie, Cathy C, Laurie, Cecelia A, Bauer, Daniel E, Conomos, Matthew P, Reiner, Alexander P, and NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium

Subjects
Quality Control, Adult, Male, Erythrocytes, base editing, Datasets as Topic, Medical and Health Sciences, Chromosomes, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, Clinical Research, and Blood Institute (U.S.), Genetics, Humans, 2.1 Biological and endogenous factors, red blood cell traits, Aetiology, Lung, Aged, Gene Editing, Genetics & Heredity, Pair 16, Human Genome, Reproducibility of Results, Genetic Variation, National Heart, Hematology, Middle Aged, Biological Sciences, United States, Phenotype, HEK293 Cells, Good Health and Well Being, whole-genome sequencing, Female, Human, Genome-Wide Association Study, Biotechnology
Abstract

Whole-genome sequencing (WGS), a powerful tool for detecting novel coding and non-coding disease-causing variants, has largely been applied to clinical diagnosis of inherited disorders. Here we leveraged WGS data in up to 62,653 ethnically diverse participants from the NHLBI Trans-Omics for Precision Medicine (TOPMed) program and assessed statistical association of variants with seven red blood cell (RBC) quantitative traits. We discovered 14 single variant-RBC trait associations at 12 genomic loci, which have not been reported previously. Several of the RBC trait-variant associations (RPN1, ELL2, MIDN, HBB, HBA1, PIEZO1, and G6PD) were replicated in independent GWAS datasets imputed to the TOPMed reference panel. Most of these discovered variants are rare/low frequency, and several are observed disproportionately among non-European Ancestry (African, Hispanic/Latino, or East Asian) populations. We identified a 3bp indel p.Lys2169del (g.88717175_88717177TCT[4]) (common only in the Ashkenazi Jewish population) of PIEZO1, a gene responsible for the Mendelian red cell disorder hereditary xerocytosis (MIM: 194380), associated with higher mean corpuscular hemoglobin concentration (MCHC). In stepwise conditional analysis and in gene-based rare variant aggregated association analysis, we identified several of the variants in HBB, HBA1, TMPRSS6, and G6PD that represent the carrier state for known coding, promoter, or splice site loss-of-function variants that cause inherited RBC disorders. Finally, we applied base and nuclease editing to demonstrate that the sentinel variant rs112097551 (nearest gene RPN1) acts through a cis-regulatory element that exerts long-range control of the gene RUVBL1 which is essential for hematopoiesis. Together, these results demonstrate the utility of WGS in ethnically diverse population-based samples and gene editing for expanding knowledge of the genetic architecture of quantitative hematologic traits and suggest a continuum between complex trait and Mendelian red cell disorders.

Published
2021

10. Robust, flexible, and scalable tests for Hardy-Weinberg equilibrium across diverse ancestries

Author

Kwong, Alan M, Blackwell, Thomas W, LeFaive, Jonathon, de Andrade, Mariza, Barnard, John, Barnes, Kathleen C, Blangero, John, Boerwinkle, Eric, Burchard, Esteban G, Cade, Brian E, Chasman, Daniel I, Chen, Han, Conomos, Matthew P, Cupples, L Adrienne, Ellinor, Patrick T, Eng, Celeste, Gao, Yan, Guo, Xiuqing, Irvin, Marguerite Ryan, Kelly, Tanika N, Kim, Wonji, Kooperberg, Charles, Lubitz, Steven A, Mak, Angel CY, Manichaikul, Ani W, Mathias, Rasika A, Montasser, May E, Montgomery, Courtney G, Musani, Solomon, Palmer, Nicholette D, Peloso, Gina M, Qiao, Dandi, Reiner, Alexander P, Roden, Dan M, Shoemaker, M Benjamin, Smith, Jennifer A, Smith, Nicholas L, Su, Jessica Lasky, Tiwari, Hemant K, Weeks, Daniel E, Weiss, Scott T, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, TOPMed Analysis Working Group, Scott, Laura J, Smith, Albert V, Abecasis, Gonçalo R, Boehnke, Michael, Kang, Hyun Min, and Beaumont, M

Subjects
Genotype, Population, population structure, Statistical, Linkage Disequilibrium, genotype likelihoods, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, Phenotype, Gene Frequency, Genetic, Models, principal components analysis, Genetics, TOPMed Analysis Working Group, Humans, next-generation sequencing, Alleles, Software, Developmental Biology
Abstract

Traditional Hardy-Weinberg equilibrium (HWE) tests (the χ2 test and the exact test) have long been used as a metric for evaluating genotype quality, as technical artifacts leading to incorrect genotype calls often can be identified as deviations from HWE. However, in data sets composed of individuals from diverse ancestries, HWE can be violated even without genotyping error, complicating the use of HWE testing to assess genotype data quality. In this manuscript, we present the Robust Unified Test for HWE (RUTH) to test for HWE while accounting for population structure and genotype uncertainty, and to evaluate the impact of population heterogeneity and genotype uncertainty on the standard HWE tests and alternative methods using simulated and real sequence data sets. Our results demonstrate that ignoring population structure or genotype uncertainty in HWE tests can inflate false-positive rates by many orders of magnitude. Our evaluations demonstrate different tradeoffs between false positives and statistical power across the methods, with RUTH consistently among the best across all evaluations. RUTH is implemented as a practical and scalable software tool to rapidly perform HWE tests across millions of markers and hundreds of thousands of individuals while supporting standard VCF/BCF formats. RUTH is publicly available at https://www.github.com/statgen/ruth.

Published
2021

11. Sequencing of 53,831 diverse genomes from the NHLBI TOPMed Program

Author

Taliun, Daniel, Harris, Daniel N, Kessler, Michael D, Carlson, Jedidiah, Szpiech, Zachary A, Torres, Raul, Taliun, Sarah A Gagliano, Corvelo, André, Gogarten, Stephanie M, Kang, Hyun Min, Pitsillides, Achilleas N, LeFaive, Jonathon, Lee, Seung-Been, Tian, Xiaowen, Browning, Brian L, Das, Sayantan, Emde, Anne-Katrin, Clarke, Wayne E, Loesch, Douglas P, Shetty, Amol C, Blackwell, Thomas W, Smith, Albert V, Wong, Quenna, Liu, Xiaoming, Conomos, Matthew P, Bobo, Dean M, Aguet, François, Albert, Christine, Alonso, Alvaro, Ardlie, Kristin G, Arking, Dan E, Aslibekyan, Stella, Auer, Paul L, Barnard, John, Barr, R Graham, Barwick, Lucas, Becker, Lewis C, Beer, Rebecca L, Benjamin, Emelia J, Bielak, Lawrence F, Blangero, John, Boehnke, Michael, Bowden, Donald W, Brody, Jennifer A, Burchard, Esteban G, Cade, Brian E, Casella, James F, Chalazan, Brandon, Chasman, Daniel I, Chen, Yii-Der Ida, Cho, Michael H, Choi, Seung Hoan, Chung, Mina K, Clish, Clary B, Correa, Adolfo, Curran, Joanne E, Custer, Brian, Darbar, Dawood, Daya, Michelle, de Andrade, Mariza, DeMeo, Dawn L, Dutcher, Susan K, Ellinor, Patrick T, Emery, Leslie S, Eng, Celeste, Fatkin, Diane, Fingerlin, Tasha, Forer, Lukas, Fornage, Myriam, Franceschini, Nora, Fuchsberger, Christian, Fullerton, Stephanie M, Germer, Soren, Gladwin, Mark T, Gottlieb, Daniel J, Guo, Xiuqing, Hall, Michael E, He, Jiang, Heard-Costa, Nancy L, Heckbert, Susan R, Irvin, Marguerite R, Johnsen, Jill M, Johnson, Andrew D, Kaplan, Robert, Kardia, Sharon LR, Kelly, Tanika, Kelly, Shannon, Kenny, Eimear E, Kiel, Douglas P, Klemmer, Robert, Konkle, Barbara A, Kooperberg, Charles, Köttgen, Anna, Lange, Leslie A, Lasky-Su, Jessica, Levy, Daniel, Lin, Xihong, Lin, Keng-Han, Liu, Chunyu, and Loos, Ruth JF

Subjects
Quality Control, Heterozygote, General Science & Technology, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, INDEL Mutation, Loss of Function Mutation, and Blood Institute (U.S.), Genetics, Humans, 2.1 Biological and endogenous factors, Polymorphism, Precision Medicine, Aetiology, Lung, Population Density, Genome, Whole Genome Sequencing, Human Genome, Genetic Variation, Genomics, Single Nucleotide, National Heart, United States, Phenotype, Good Health and Well Being, Cytochrome P-450 CYP2D6, Haplotypes, Mutagenesis, Sample Size, Generic health relevance, Human, Biotechnology
Abstract

The Trans-Omics for Precision Medicine (TOPMed) programme seeks to elucidate the genetic architecture and biology of heart, lung, blood and sleep disorders, with the ultimate goal of improving diagnosis, treatment and prevention of these diseases. The initial phases of the programme focused on whole-genome sequencing of individuals with rich phenotypic data and diverse backgrounds. Here we describe the TOPMed goals and design as well as the available resources and early insights obtained from the sequence data. The resources include a variant browser, a genotype imputation server, and genomic and phenotypic data that are available through dbGaP (Database of Genotypes and Phenotypes)1. In the first 53,831 TOPMed samples, we detected more than 400million single-nucleotide and insertion or deletion variants after alignment with the reference genome. Additional previously undescribed variants were detected through assembly of unmapped reads and customized analysis in highly variable loci. Among the more than 400million detected variants, 97% have frequencies of less than 1% and 46% are singletons that are present in only one individual (53% among unrelated individuals). These rare variants provide insights into mutational processes and recent human evolutionary history. The extensive catalogue of genetic variation in TOPMed studies provides unique opportunities for exploring the contributions of rare and noncoding sequence variants to phenotypic variation. Furthermore, combining TOPMed haplotypes with modern imputation methods improves the power and reach of genome-wide association studies to include variants down to a frequency of approximately 0.01%.

Published
2021

12. Novel genetic determinants of telomere length from a multi-ethnic analysis of 75,000 whole genome sequences in TOPMed

Author

Taub, Margaret A, Weinstock, Joshua S, Iyer, Kruthika R, Yanek, Lisa R, Conomos, Matthew P, Brody, Jennifer A, Keramati, Ali, Laurie, Cecelia A, Arvanitis, Marios, Smith, Albert V, Lane, John, Becker, Lewis C, Bis, Joshua C, Blangero, John, Bleecker, Eugene R, Burchard, Esteban G, Celedon, Juan C, Chang, Yen Pei C, Custer, Brian, Darbar, Dawood, de las Fuentes, Lisa, DeMeo, Dawn L, Freedman, Barry I, Garrett, Melanie E, Gladwin, Mark T, Heckbert, Susan R, Hidalgo, Bertha A, Ingram, Christie, Irvin, Marguerite R, Craig Johnson, W, Kaab, Stefan, Launer, Lenore, Lee, Jiwon, Liu, Simin, Moscati, Arden, North, Kari E, Peyser, Patricia A, Rafaels, Nicholas, Raffield, Laura M, Weeks, Daniel E, Wheeler, Marsha M, Keoki Williams, L., Zhao, Wei, Armanios, Mary, Aslibekyan, Stella, Auer, Paul L, Bowden, Donald W, Cade, Brian E, Yii-Der Chen, Ida, Cho, Michael H, Cupples, L Adrienne, Curran, Joanne E, Daya, Michelle, Deka, Ranjan, Guo, Xiuqing, Hou, Lifang, Hwang, Shih-Jen, Johnsen, Jill M, Kenny, Eimear E, Levin, Albert M, Liu, Chunyu, Minster, Ryan L, Nouraie, Mehdi, Sabino, Ester C, Smith, Jennifer A, Smith, Nicholas L, Lasky Su, Jessica, Telen, Marilyn J, Tiwari, Hemant K, Tracy, Russell P, White, Marquitta J, Zhang, Yingze, Wiggins, Kerri L, Weiss, Scott T, Vasan, Ramachandran S, Taylor, Kent D, Sinner, Moritz F, Silverman, Edwin K, Benjamin Shoemaker, M., Sheu, Wayne H-H, Rotter, Jerome I, Redline, Susan, Psaty, Bruce M, Peralta, Juan M, Palmer, Nicholette D, Loos, Ruth JF, Montgomery, Courtney G, Mitchell, Braxton D, Meyers, Deborah A, McGarvey, Stephen T, Mak, Angel CY, Kumar, Rajesh, Kooperberg, Charles, Konkle, Barbara A, Kelly, Shannon, Kardia, Sharon LR, Kaplan, Robert, He, Jiang, Gui, Hongsheng, Fornage, Myriam, Ellinor, Patrick T, de Andrade, Mariza, Correa, Adolfo, Boerwinkle, Eric, Barnes, Kathleen C, Ashley-Koch, Allison E, Arnett, Donna K, Albert, Christine, Laurie, Cathy C, Abecasis, Goncalo, Aviv, Abraham, Nickerson, Deborah A, Wilson, James G, Rich, Stephen S, Levy, Daniel, Battle, Alexis, Blackwell, Thomas W, Ruczinski, Ingo, Thornton, Timothy, O’Connell, Jeff, Perry, James A, Pankratz, Nathan, Reiner, Alexander P, and Mathias, Rasika A

Abstract

Telomeres shorten in replicating somatic cells and with age; in human leukocytes, telomere length (TL) is associated with a host of aging-related diseases 1,2 . To date, 16 genome-wide association studies (GWAS) have identified twenty-three loci associated with leukocyte TL 3–18 , but prior studies were primarily in individuals of European and Asian ancestry and relied on laboratory assays including Southern Blot and qPCR to quantify TL. Here, we estimated TL bioinformatically, leveraging whole genome sequencing (WGS) of whole blood from n=75,176 subjects in the Trans-Omics for Precision Medicine (TOPMed) Program. We performed the largest multi-ethnic and only WGS-based genome-wide association analysis of TL to date. We identified 22 associated loci (p-value

Published
2019
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13. Exome sequencing of 20,791 cases of type 2 diabetes and 24,440 controls

Author

Flannick, Jason, Mercader, Josep M, Fuchsberger, Christian, Udler, Miriam S, Mahajan, Anubha, Wessel, Jennifer, Teslovich, Tanya M, Caulkins, Lizz, Koesterer, Ryan, Barajas-Olmos, Francisco, Blackwell, Thomas W, Boerwinkle, Eric, Brody, Jennifer A, Centeno-Cruz, Federico, Chen, Ling, Chen, Siying, Contreras-Cubas, Cecilia, Córdova, Emilio, Correa, Adolfo, Cortes, Maria, DeFronzo, Ralph A, Dolan, Lawrence, Drews, Kimberly L, Elliott, Amanda, Floyd, James S, Gabriel, Stacey, Garay-Sevilla, Maria Eugenia, García-Ortiz, Humberto, Gross, Myron, Han, Sohee, Heard-Costa, Nancy L, Jackson, Anne U, Jørgensen, Marit E, Kang, Hyun Min, Kelsey, Megan, Kim, Bong-Jo, Koistinen, Heikki A, Kuusisto, Johanna, Leader, Joseph B, Linneberg, Allan, Liu, Ching-Ti, Liu, Jianjun, Lyssenko, Valeriya, Manning, Alisa K, Marcketta, Anthony, Malacara-Hernandez, Juan Manuel, Martínez-Hernández, Angélica, Matsuo, Karen, Mayer-Davis, Elizabeth, Mendoza-Caamal, Elvia, Mohlke, Karen L, Morrison, Alanna C, Ndungu, Anne, Ng, Maggie CY, O'Dushlaine, Colm, Payne, Anthony J, Pihoker, Catherine, Broad Genomics Platform, Post, Wendy S, Preuss, Michael, Psaty, Bruce M, Vasan, Ramachandran S, Rayner, N William, Reiner, Alexander P, Revilla-Monsalve, Cristina, Robertson, Neil R, Santoro, Nicola, Schurmann, Claudia, So, Wing Yee, Soberón, Xavier, Stringham, Heather M, Strom, Tim M, Tam, Claudia HT, Thameem, Farook, Tomlinson, Brian, Torres, Jason M, Tracy, Russell P, van Dam, Rob M, Vujkovic, Marijana, Wang, Shuai, Welch, Ryan P, Witte, Daniel R, Wong, Tien-Yin, Atzmon, Gil, Barzilai, Nir, Blangero, John, Bonnycastle, Lori L, Bowden, Donald W, Chambers, John C, Chan, Edmund, Cheng, Ching-Yu, Cho, Yoon Shin, Collins, Francis S, de Vries, Paul S, Duggirala, Ravindranath, Glaser, Benjamin, Gonzalez, Clicerio, Gonzalez, Ma Elena, Groop, Leif, and Kooner, Jaspal Singh

Subjects
Male, General Science & Technology, Knockout, LuCamp, Whole Exome Sequencing, Decision Support Techniques, Mice, T2D-GENES, Gene Frequency, Exome Sequencing, Diabetes Mellitus, Genetics, Animals, Humans, 2.1 Biological and endogenous factors, AMP-T2D-GENES, Exome, Aetiology, ESP, Metabolic and endocrine, Broad Genomics Platform, Prevention, Diabetes, Human Genome, ProDiGY, Case-Control Studies, DiscovEHR Collaboration, SIGMA-T2D, Female, CHARGE, Type 2, GoT2D, Genome-Wide Association Study, Biotechnology
Abstract

Protein-coding genetic variants that strongly affect disease risk can yield relevant clues to disease pathogenesis. Here we report exome-sequencing analyses of 20,791individuals with type 2 diabetes (T2D) and 24,440non-diabetic control participants from 5ancestries. We identify gene-level associations of rare variants (with minor allele frequencies of less than 0.5%) in 4genes at exome-wide significance, including a series of more than 30SLC30A8 alleles that conveys protection against T2D, and in 12gene sets, including those corresponding to T2D drug targets (P=6.1×10-3) and candidate genes from knockout mice (P=5.2×10-3). Within our study, the strongest T2D gene-level signals for rare variants explain at most 25% of the heritability of the strongest common single-variant signals, and the gene-level effect sizes of the rare variants that we observed in established T2D drug targets will require 75,000-185,000sequenced cases to achieve exome-wide significance. We propose a method to interpret these modest rare-variant associations and to incorporate these associations into future target or gene prioritization efforts.

Published
2019

14. Erratum: Sequence data and association statistics from 12,940 type 2 diabetes cases and controls

Author

Flannick, Jason, Fuchsberger, Christian, Mahajan, Anubha, Teslovich, Tanya M, Agarwala, Vineeta, Gaulton, Kyle J, Caulkins, Lizz, Koesterer, Ryan, Ma, Clement, Moutsianas, Loukas, McCarthy, Davis J, Rivas, Manuel A, Perry, John RB, Sim, Xueling, Blackwell, Thomas W, Robertson, Neil R, Rayner, N William, Cingolani, Pablo, Locke, Adam E, Tajes, Juan Fernandez, Highland, Heather M, Dupuis, Josee, Chines, Peter S, Lindgren, Cecilia M, Hartl, Christopher, Jackson, Anne U, Chen, Han, Huyghe, Jeroen R, van de Bunt, Martijn, Pearson, Richard D, Kumar, Ashish, Müller-Nurasyid, Martina, Grarup, Niels, Stringham, Heather M, Gamazon, Eric R, Lee, Jaehoon, Chen, Yuhui, Scott, Robert A, Below, Jennifer E, Chen, Peng, Huang, Jinyan, Go, Min Jin, Stitzel, Michael L, Pasko, Dorota, Parker, Stephen CJ, Varga, Tibor V, Green, Todd, Beer, Nicola L, Day-Williams, Aaron G, Ferreira, Teresa, Fingerlin, Tasha, Horikoshi, Momoko, Hu, Cheng, Huh, Iksoo, Ikram, Mohammad Kamran, Kim, Bong-Jo, Kim, Yongkang, Kim, Young Jin, Kwon, Min-Seok, Lee, Juyoung, Lee, Selyeong, Lin, Keng-Han, Maxwell, Taylor J, Nagai, Yoshihiko, Wang, Xu, Welch, Ryan P, Yoon, Joon, Zhang, Weihua, Barzilai, Nir, Voight, Benjamin F, Han, Bok-Ghee, Jenkinson, Christopher P, Kuulasmaa, Teemu, Kuusisto, Johanna, Manning, Alisa, Ng, Maggie CY, Palmer, Nicholette D, Balkau, Beverley, Stančáková, Alena, Abboud, Hanna E, Boeing, Heiner, Giedraitis, Vilmantas, Prabhakaran, Dorairaj, Gottesman, Omri, Scott, James, Carey, Jason, Kwan, Phoenix, Grant, George, Smith, Joshua D, Neale, Benjamin M, Purcell, Shaun, Butterworth, Adam S, Howson, Joanna MM, Lee, Heung Man, Lu, Yingchang, Kwak, Soo-Heon, Zhao, Wei, Danesh, John, and Lam, Vincent KL

Abstract

This corrects the article DOI: 10.1038/sdata.2017.179.

Published
2018

15. Sequence data and association statistics from 12,940 type 2 diabetes cases and controls

Author

Flannick, Jason, Fuchsberger, Christian, Mahajan, Anubha, Teslovich, Tanya M, Agarwala, Vineeta, Gaulton, Kyle J, Caulkins, Lizz, Koesterer, Ryan, Ma, Clement, Moutsianas, Loukas, McCarthy, Davis J, Rivas, Manuel A, Perry, John RB, Sim, Xueling, Blackwell, Thomas W, Robertson, Neil R, Rayner, N William, Cingolani, Pablo, Locke, Adam E, Tajes, Juan Fernandez, Highland, Heather M, Dupuis, Josee, Chines, Peter S, Lindgren, Cecilia M, Hartl, Christopher, Jackson, Anne U, Chen, Han, Huyghe, Jeroen R, van de Bunt, Martijn, Pearson, Richard D, Kumar, Ashish, Müller-Nurasyid, Martina, Grarup, Niels, Stringham, Heather M, Gamazon, Eric R, Lee, Jaehoon, Chen, Yuhui, Scott, Robert A, Below, Jennifer E, Chen, Peng, Huang, Jinyan, Go, Min Jin, Stitzel, Michael L, Pasko, Dorota, Parker, Stephen CJ, Varga, Tibor V, Green, Todd, Beer, Nicola L, Day-Williams, Aaron G, Ferreira, Teresa, Fingerlin, Tasha, Horikoshi, Momoko, Hu, Cheng, Huh, Iksoo, Ikram, Mohammad Kamran, Kim, Bong-Jo, Kim, Yongkang, Kim, Young Jin, Kwon, Min-Seok, Lee, Juyoung, Lee, Selyeong, Lin, Keng-Han, Maxwell, Taylor J, Nagai, Yoshihiko, Wang, Xu, Welch, Ryan P, Yoon, Joon, Zhang, Weihua, Barzilai, Nir, Voight, Benjamin F, Han, Bok-Ghee, Jenkinson, Christopher P, Kuulasmaa, Teemu, Kuusisto, Johanna, Manning, Alisa, Ng, Maggie CY, Palmer, Nicholette D, Balkau, Beverley, Stančáková, Alena, Abboud, Hanna E, Boeing, Heiner, Giedraitis, Vilmantas, Prabhakaran, Dorairaj, Gottesman, Omri, Scott, James, Carey, Jason, Kwan, Phoenix, Grant, George, Smith, Joshua D, Neale, Benjamin M, Purcell, Shaun, Butterworth, Adam S, Howson, Joanna MM, Lee, Heung Man, Lu, Yingchang, Kwak, Soo-Heon, Zhao, Wei, Danesh, John, and Lam, Vincent KL

Subjects
European Continental Ancestry Group, Diabetes, Human Genome, Diabetes Mellitus, Genetics, Humans, Genetic Variation, 2.1 Biological and endogenous factors, Aetiology, White People, Type 2, Metabolic and endocrine
Abstract

To investigate the genetic basis of type 2 diabetes (T2D) to high resolution, the GoT2D and T2D-GENES consortia catalogued variation from whole-genome sequencing of 2,657 European individuals and exome sequencing of 12,940 individuals of multiple ancestries. Over 27M SNPs, indels, and structural variants were identified, including 99% of low-frequency (minor allele frequency [MAF] 0.1-5%) non-coding variants in the whole-genome sequenced individuals and 99.7% of low-frequency coding variants in the whole-exome sequenced individuals. Each variant was tested for association with T2D in the sequenced individuals, and, to increase power, most were tested in larger numbers of individuals (>80% of low-frequency coding variants in ~82 K Europeans via the exome chip, and ~90% of low-frequency non-coding variants in ~44 K Europeans via genotype imputation). The variants, genotypes, and association statistics from these analyses provide the largest reference to date of human genetic information relevant to T2D, for use in activities such as T2D-focused genotype imputation, functional characterization of variants or genes, and other novel analyses to detect associations between sequence variation and T2D.

Published
2017

16. A Low-Frequency Inactivating AKT2 Variant Enriched in the Finnish Population Is Associated With Fasting Insulin Levels and Type 2 Diabetes Risk

Author

Manning, Alisa, Highland, Heather M, Gasser, Jessica, Sim, Xueling, Tukiainen, Taru, Fontanillas, Pierre, Grarup, Niels, Rivas, Manuel A, Mahajan, Anubha, Locke, Adam E, Cingolani, Pablo, Pers, Tune H, Viñuela, Ana, Brown, Andrew A, Wu, Ying, Flannick, Jason, Fuchsberger, Christian, Gamazon, Eric R, Gaulton, Kyle J, Im, Hae Kyung, Teslovich, Tanya M, Blackwell, Thomas W, Bork-Jensen, Jette, Burtt, Noël P, Chen, Yuhui, Green, Todd, Hartl, Christopher, Kang, Hyun Min, Kumar, Ashish, Ladenvall, Claes, Ma, Clement, Moutsianas, Loukas, Pearson, Richard D, Perry, John RB, Rayner, N William, Robertson, Neil R, Scott, Laura J, van de Bunt, Martijn, Eriksson, Johan G, Jula, Antti, Koskinen, Seppo, Lehtimäki, Terho, Palotie, Aarno, Raitakari, Olli T, Jacobs, Suzanne BR, Wessel, Jennifer, Chu, Audrey Y, Scott, Robert A, Goodarzi, Mark O, Blancher, Christine, Buck, Gemma, Buck, David, Chines, Peter S, Gabriel, Stacey, Gjesing, Anette P, Groves, Christopher J, Hollensted, Mette, Huyghe, Jeroen R, Jackson, Anne U, Jun, Goo, Justesen, Johanne Marie, Mangino, Massimo, Murphy, Jacquelyn, Neville, Matt, Onofrio, Robert, Small, Kerrin S, Stringham, Heather M, Trakalo, Joseph, Banks, Eric, Carey, Jason, Carneiro, Mauricio O, DePristo, Mark, Farjoun, Yossi, Fennell, Timothy, Goldstein, Jacqueline I, Grant, George, Hrabé de Angelis, Martin, Maguire, Jared, Neale, Benjamin M, Poplin, Ryan, Purcell, Shaun, Schwarzmayr, Thomas, Shakir, Khalid, Smith, Joshua D, Strom, Tim M, Wieland, Thomas, Lindstrom, Jaana, Brandslund, Ivan, Christensen, Cramer, Surdulescu, Gabriela L, Lakka, Timo A, Doney, Alex SF, Nilsson, Peter, Wareham, Nicholas J, Langenberg, Claudia, Varga, Tibor V, Franks, Paul W, Rolandsson, Olov, Rosengren, Anders H, and Farook, Vidya S

Subjects
Genotype, Diabetes, Fasting, Hispanic or Latino, Medical and Health Sciences, White People, Black or African American, Endocrinology & Metabolism, Gene Frequency, Asian People, Case-Control Studies, Diabetes Mellitus, Odds Ratio, Genetics, Humans, Insulin, 2.1 Biological and endogenous factors, Genetic Predisposition to Disease, Insulin Resistance, Aetiology, Proto-Oncogene Proteins c-akt, Type 2, Alleles, Finland, Metabolic and endocrine
Abstract

To identify novel coding association signals and facilitate characterization of mechanisms influencing glycemic traits and type 2 diabetes risk, we analyzed 109,215 variants derived from exome array genotyping together with an additional 390,225 variants from exome sequence in up to 39,339 normoglycemic individuals from five ancestry groups. We identified a novel association between the coding variant (p.Pro50Thr) in AKT2 and fasting plasma insulin (FI), a gene in which rare fully penetrant mutations are causal for monogenic glycemic disorders. The low-frequency allele is associated with a 12% increase in FI levels. This variant is present at 1.1% frequency in Finns but virtually absent in individuals from other ancestries. Carriers of the FI-increasing allele had increased 2-h insulin values, decreased insulin sensitivity, and increased risk of type 2 diabetes (odds ratio 1.05). In cellular studies, the AKT2-Thr50 protein exhibited a partial loss of function. We extend the allelic spectrum for coding variants in AKT2 associated with disorders of glucose homeostasis and demonstrate bidirectional effects of variants within the pleckstrin homology domain of AKT2.

Published
2017

17. Data Descriptor : Sequence data and association statistics from 12,940 type 2 diabetes cases and controls

Author

Flannick, Jason, Fuchsberger, Christian, Mahajan, Anubha, Teslovich, Tanya M., Agarwala, Vineeta, Gaulton, Kyle J., Caulkins, Lizz, Koesterer, Ryan, Ma, Clement, Moutsianas, Loukas, McCarthy, Davis J., Rivas, Manuel A., Perry, John R.B., Sim, Xueling, Blackwell, Thomas W., Robertson, Neil R., Rayner, N. William, Cingolani, Pablo, Locke, Adam E., Tajes, Juan Fernandez, Highland, Heather M., Dupuis, Josée, Chines, Peter S., Lindgren, Cecilia M., Hartl, Christopher, Jackson, Anne U., Chen, Han, Huyghe, Jeroen R., Van De Bunt, Martijn, Pearson, Richard D., Kumar, Ashish, Müller-Nurasyid, Martina, Grarup, Niels, Stringham, Heather M., Gamazon, Eric R., Lee, Jaehoon, Chen, Yuhui, Scott, Robert A., Below, Jennifer E., Chen, Peng, Huang, Jinyan, Go, Min Jin, Stitzel, Michael L., Pasko, Dorota, Parker, Stephen C.J., Varga, Tibor V., Green, Todd, Beer, Nicola L., Day-Williams, Aaron G., Ferreira, Teresa, Fingerlin, Tasha, Horikoshi, Momoko, Hu, Cheng, Huh, Iksoo, Ikram, Mohammad Kamran, Kim, Bong Jo, Kim, Yongkang, Kim, Young Jin, Kwon, Min Seok, Lee, Juyoung, Lee, Selyeong, Lin, Keng Han, Maxwell, Taylor J., Nagai, Yoshihiko, Wang, Xu, Welch, Ryan P., Yoon, Joon, Zhang, Weihua, Barzilai, Nir, Voight, Benjamin F., Han, Bok Ghee, Jenkinson, Christopher P., Kuulasmaa, Teemu, Kuusisto, Johanna, Manning, Alisa, Ng, Maggie C.Y., Palmer, Nicholette D., Balkau, Beverley, Stančáková, Alena, Abboud, Hanna E., Boeing, Heiner, Giedraitis, Vilmantas, Prabhakaran, Dorairaj, Gottesman, Omri, Scott, James, Carey, Jason, Kwan, Phoenix, Grant, George, Smith, Joshua D., Neale, Benjamin M., Purcell, Shaun, Butterworth, Adam S., Howson, Joanna M.M., Lee, Heung Man, Lu, Yingchang, Kwak, Soo Heon, Zhao, Wei, Danesh, John, Lam, Vincent K.L., Park, Kyong Soo, Saleheen, Danish, So, Wing Yee, Tam, Claudia H.T., Afzal, Uzma, Aguilar, David, Arya, Rector, Aung, Tin, Chan, Edmund, Navarro, Carmen, Cheng, Ching Yu, Palli, Domenico, Correa, Adolfo, Curran, Joanne E., Rybin, Dennis, Farook, Vidya S., Fowler, Sharon P., Freedman, Barry I., Griswold, Michael, Hale, Daniel Esten, Hicks, Pamela J., Khor, Chiea Chuen, Kumar, Satish, Lehne, Benjamin, Thuillier, Dorothée, Lim, Wei Yen, Liu, Jianjun, Loh, Marie, Musani, Solomon K., Puppala, Sobha, Scott, William R., Yengo, Loïc, Tan, Sian Tsung, Taylor, Herman A., Thameem, Farook, Wilson, Gregory, Wong, Tien Yin, Njølstad, Pål Rasmus, Levy, Jonathan C., Mangino, Massimo, Bonnycastle, Lori L., Schwarzmayr, Thomas, Fadista, João, Surdulescu, Gabriela L., Herder, Christian, Groves, Christopher J., Wieland, Thomas, Bork-Jensen, Jette, Brandslund, Ivan, Christensen, Cramer, Koistinen, Heikki A., Doney, Alex S.F., Kinnunen, Leena, Esko, Tõnu, Farmer, Andrew J., Hakaste, Liisa, Hodgkiss, Dylan, Kravic, Jasmina, Lyssenko, Valeriya, Hollensted, Mette, Jørgensen, Marit E., Jørgensen, Torben, Ladenvall, Claes, Justesen, Johanne Marie, Käräjämäki, Annemari, Kriebel, Jennifer, Rathmann, Wolfgang, Lannfelt, Lars, Lauritzen, Torsten, Narisu, Narisu, Linneberg, Allan, Melander, Olle, Milani, Lili, Neville, Matt, Orho-Melander, Marju, Qi, Lu, Qi, Qibin, Roden, Michael, Rolandsson, Olov, Swift, Amy, Rosengren, Anders H., Stirrups, Kathleen, Wood, Andrew R., Mihailov, Evelin, Blancher, Christine, Carneiro, Mauricio O., Maguire, Jared, Poplin, Ryan, Shakir, Khalid, Fennell, Timothy, DePristo, Mark, De Angelis, Martin Hrabé, Deloukas, Panos, Gjesing, Anette P., Jun, Goo, Nilsson, Peter M., Murphy, Jacquelyn, Onofrio, Robert, Thorand, Barbara, Hansen, Torben, Meisinger, Christa, Hu, Frank B., Isomaa, Bo, Karpe, Fredrik, Liang, Liming, Peters, Annette, Huth, Cornelia, O'Rahilly, Stephen P., Palmer, Colin N.A., Pedersen, Oluf, Rauramaa, Rainer, Tuomilehto, Jaakko, Salomaa, Veikko, Watanabe, Richard M., Syvänen, Ann Christine, Bergman, Richard N., Bharadwaj, Dwaipayan, Bottinger, Erwin P., Cho, Yoon Shin, Chandak, Giriraj R., Chan, Juliana C.N., Chia, Kee Seng, Daly, Mark J., Ebrahim, Shah B., Langenberg, Claudia, Elliott, Paul, Jablonski, Kathleen A., Lehman, Donna M., Jia, Weiping, Ma, Ronald C.W., Pollin, Toni I., Sandhu, Manjinder, Tandon, Nikhil, Froguel, Philippe, Barroso, Inês, Teo, Yik Ying, Zeggini, Eleftheria, Loos, Ruth J.F., Small, Kerrin S., Ried, Janina S., DeFronzo, Ralph A., Grallert, Harald, Glaser, Benjamin, Metspalu, Andres, Wareham, Nicholas J., Walker, Mark, Banks, Eric, Gieger, Christian, Ingelsson, Erik, Im, Hae Kyung, Illig, Thomas, Franks, Paul W., Buck, Gemma, Trakalo, Joseph, Buck, David, Prokopenko, Inga, Mägi, Reedik, Lind, Lars, Farjoun, Yossi, Owen, Katharine R., Gloyn, Anna L., Strauch, Konstantin, Tuomi, Tiinamaija, Kooner, Jaspal Singh, Lee, Jong Young, Park, Taesung, Donnelly, Peter, Morris, Andrew D., Hattersley, Andrew T., Bowden, Donald W., Collins, Francis S., Atzmon, Gil, Chambers, John C., Spector, Timothy D., Laakso, Markku, Strom, Tim M., Bell, Graeme I., Blangero, John, Duggirala, Ravindranath, Tai, Eshyong, McVean, Gilean, Hanis, Craig L., Wilson, James G., Seielstad, Mark, Frayling, Timothy M., Meigs, James B., Cox, Nancy J., Sladek, Rob, Lander, Eric S., Gabriel, Stacey, Mohlke, Karen L., Meitinger, Thomas, Groop, Leif, Abecasis, Goncalo, Scott, Laura J., Morris, Andrew P., Kang, Hyun Min, Altshuler, David, Burtt, Noël P., Florez, Jose C., Boehnke, Michael, McCarthy, Mark I., Clinicum, Department of Medicine, Endokrinologian yksikkö, Research Programs Unit, Diabetes and Obesity Research Program, Institute for Molecular Medicine Finland, HUS Internal Medicine and Rehabilitation, and HUS Abdominal Center

Subjects
MUTATIONS, COMMON DISEASES, POPULATION-SCALE, Endocrinology and Diabetes, FRAMEWORK, GENETIC ARCHITECTURE, RARE VARIANTS, DISCOVERY, 3121 General medicine, internal medicine and other clinical medicine, Endokrinologi och diabetes, IMPUTATION, GENOME-WIDE ASSOCIATION, Medical Genetics, METAANALYSIS, Medicinsk genetik
Abstract

Correction: SCIENTIFIC DATA Vol. 5, Article Number: 180182, DOI: 10.1038/sdata.2018.2 Published: JAN 23 2018 To investigate the genetic basis of type 2 diabetes (T2D) to high resolution, the GoT2D and T2D-GENES consortia catalogued variation from whole-genome sequencing of 2,657 European individuals and exome sequencing of 12,940 individuals of multiple ancestries. Over 27M SNPs, indels, and structural variants were identified, including 99% of low-frequency (minor allele frequency [MAF] 0.1-5%) non-coding variants in the whole-genome sequenced individuals and 99.7% of low-frequency coding variants in the whole-exome sequenced individuals. Each variant was tested for association with T2D in the sequenced individuals, and, to increase power, most were tested in larger numbers of individuals (> 80% of low-frequency coding variants in similar to 82 K Europeans via the exome chip, and similar to 90% of low-frequency non-coding variants in similar to 44 K Europeans via genotype imputation). The variants, genotypes, and association statistics from these analyses provide the largest reference to date of human genetic information relevant to T2D, for use in activities such as T2D-focused genotype imputation, functional characterization of variants or genes, and other novel analyses to detect associations between sequence variation and T2D.

Published
2017
Full Text
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18. Identification and Functional Characterization of G6PC2 Coding Variants Influencing Glycemic Traits Define an Effector Transcript at the G6PC2-ABCB11 Locus

Author

Mahajan, Anubha, Sim, Xueling, Ng, Hui Jin, Manning, Alisa, Rivas, Manuel A., Highland, Heather M., Locke, Adam E., Grarup, Niels, Im, Hae Kyung, Cingolani, Pablo, Flannick, Jason, Fontanillas, Pierre, Fuchsberger, Christian, Gaulton, Kyle J., Teslovich, Tanya M., Rayner, N. William, Robertson, Neil R., Beer, Nicola L., Rundle, Jana K., Bork-Jensen, Jette, Ladenvall, Claes, Blancher, Christine, Buck, David, Buck, Gemma, Burtt, Noël P., Gabriel, Stacey, Gjesing, Anette P., Groves, Christopher J., Hollensted, Mette, Huyghe, Jeroen R., Jackson, Anne U., Jun, Goo, Justesen, Johanne Marie, Mangino, Massimo, Murphy, Jacquelyn, Neville, Matt, Onofrio, Robert, Small, Kerrin S., Stringham, Heather M., Syvänen, Ann Christine, Trakalo, Joseph, Abecasis, Goncalo, Bell, Graeme I., Blangero, John, Cox, Nancy J., Duggirala, Ravindranath, Hanis, Craig L., Seielstad, Mark, Wilson, James G., Christensen, Cramer, Brandslund, Ivan, Rauramaa, Rainer, Surdulescu, Gabriela L., Doney, Alex S F, Lannfelt, Lars, Linneberg, Allan, Isomaa, Bo, Tuomi, Tiinamaija, Jørgensen, Marit E., Jørgensen, Torben, Kuusisto, Johanna, Uusitupa, Matti, Salomaa, Veikko, Spector, Timothy D., Morris, Andrew D., Palmer, Colin N A, Collins, Francis S., Mohlke, Karen L., Bergman, Richard N., Ingelsson, Erik, Lind, Lars, Tuomilehto, Jaakko, Hansen, Torben, Watanabe, Richard M., Prokopenko, Inga, Dupuis, Josee, Karpe, Fredrik, Groop, Leif, Laakso, Markku, Pedersen, Oluf, Florez, Jose C., Morris, Andrew P., Altshuler, David, Meigs, James B., Boehnke, Michael, McCarthy, Mark I., Lindgren, Cecilia M., Gloyn, Anna L., Abboud, Hanna E., Afzal, Uzma, Aguilar, David, Arya, Rector, Atzmon, Gil, Aung, Tin, Banks, Eric, Barroso, Inês, Barzilai, Nir, Below, Jennifer E., Bharadwaj, Dwaipayan, Blackwell, Thomas W., Bonnycastle, Lori L., Bowden, Don, Carey, Jason, Carneiro, Mauricio O., Chambers, John C., Chan, Edmund, Chan, Juliana, Chandak, Giriraj R., Chen, Peng, Chen, Yuhui, Chen, Han, Cheng, Ching Yu, Chia, Kee Seng, Cho, Yoon Shin, Correa, Adolfo, Curran, Joanne E., Daly, Mark J., Day-Williams, Aaron G., DeFronzo, Ralph A., DePristo, Mark, Donnelly, Peter J., Ebrahim, Shah B., Elliott, Paul, Esko, Tõnu, Fadista, João, Farjoun, Yossi, Farmer, Andrew J., Farook, Vidya S., Fennell, Timothy, Ferreira, Teresa, Fingerlin, Tasha, Forsén, Tom, Fowler, Sharon P., Franks, Paul W., Frayling, Timothy M., Freedman, Barry I., Froguel, Philippe, Gamazon, Eric R., Gieger, Christian, Glaser, Benjamin, Go, Min Jin, Goldstein, Jacqueline I., Grallert, Harald, Grant, George, Green, Todd, Griswold, Michael, Hale, Daniel Esten, Han, Bok Ghee, Hartl, Christopher, Hattersley, Andrew T., Hicks, Pamela J., Hodgkiss, Dylan, Horikoshi, Momoko, Hrabé de Angelis, Martin, Hu, Cheng, Hu, Frank B., Huh, Iksoo, Kamran Ikram, Mohammad, Illig, Thomas, Jablonski, Kathleen A., Jenkinson, Christopher P., Jia, Weiping, Kang, Hyun Min, Khor, Chiea Chuen, Kim, Yongkang, Kim, Young Jin, Kim, Bong Jo, Kinnunen, Leena, Kooner, Jaspal Singh, Kravic, Jasmina, Kriebel, Jennifer, Kumar, Ashish, Kumar, Satish, Kuulasmaa, Teemu, Kwon, Min Seok, Langenberg, Claudia, Lauritzen, Torsten, Lee, Selyeong, Lee, Jaehoon, Lee, Juyoung, Lee, Jong Young, Lehman, Donna M., Lehne, Benjamin, Levy, Jonathan C., Li, Jiang, Liang, Liming, Lim, Wei Yen, Lin, Keng Han, Liu, Jianjun, Loh, Marie, Ma, Ronald C W, Ma, Clement, Mägi, Reedik, Maguire, Jared, Maxwell, Taylor J., McVean, Gilean, Meisinger, Christa, Meitinger, Thomas, Melander, Olle, Metspalu, Andres, Mihailov, Evelin, Milani, Lili, Moutsianas, Loukas, Müller-Nurasyid, Martina, K. Musani, Solomon, Nagai, Yoshihiko, Narisu, Narisu, Neale, Benjamin M., Ng, Maggie C Y, Nilsson, Peter, O'Rahilly, Stephen P., Orho-Melander, Marju, Owen, Katharine R., Palmer, Nicholette D., Park, Taesung, Pasko, Dorota, Pearson, Richard D., Perry, John R B, Peters, Annette, Pollin, Toni I., Poplin, Ryan, Prabhakaran, Dorairaj, Puppala, Sobha, Purcell, Shaun, Qi, Lu, Qi, Qibin, Roden, Michael, Rolandsson, Olov, Rosengren, Anders H., Sandhu, Manjinder, Schwarzmayr, Thomas, Scott, Laura J., Scott, Robert A., Scott, James, Scott, William R., Sehmi, Jobanpreet, Shakir, Khalid, Sladek, Rob, Smith, Joshua D., Stancáková, Alena, Strauch, Konstantin, Strom, Tim M., Swift, Amy, Tai, E. Shyong, Tajes, Juan Fernandez, Tan, Sian Tsung, Tandon, Nikhil, Taylor, Herman A., Teo, Yik Ying, Thameem, Farook, Thorand, Barbara, van de Bunt, Martijn, Varga, Tibor V., Walker, Mark, Wareham, Nicholas J., Welch, Ryan P., Wieland, Thomas, Wilson, Gregory, Wong, Tien Yin, Wood, Andrew R., Yoon, Joon, Zeggini, Eleftheria, and Zhang, Weihua

Abstract

Genome wide association studies (GWAS) for fasting glucose (FG) and insulin (FI) have identified common variant signals which explain 4.8% and 1.2% of trait variance, respectively. It is hypothesized that low-frequency and rare variants could contribute substantially to unexplained genetic variance. To test this, we analyzed exome-array data from up to 33,231 non-diabetic individuals of European ancestry. We found exome-wide significant (P

Published
2015
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19. Whole genome sequence analysis of platelet traits in the NHLBI Trans-Omics for Precision Medicine (TOPMed) initiative

Author

Little, Amarise, Hu, Yao, Sun, Quan, Jain, Deepti, Broome, Jai, Chen, Ming-Huei, Thibord, Florian, McHugh, Caitlin, Surendran, Praveen, Blackwell, Thomas W, Brody, Jennifer A, Bhan, Arunoday, Chami, Nathalie, De Vries, Paul S, Ekunwe, Lynette, Heard-Costa, Nancy, Hobbs, Brian D, Manichaikul, Ani, Moon, Jee-Young, Preuss, Michael H, Ryan, Kathleen, Wang, Zhe, Wheeler, Marsha, Yanek, Lisa R, Abecasis, Goncalo R, Almasy, Laura, Beaty, Terri H, Becker, Lewis C, Blangero, John, Boerwinkle, Eric, Butterworth, Adam S, Choquet, Hélène, Correa, Adolfo, Curran, Joanne E, Faraday, Nauder, Fornage, Myriam, Glahn, David C, Hou, Lifang, Jorgenson, Eric, Kooperberg, Charles, Lewis, Joshua P, Lloyd-Jones, Donald M, Loos, Ruth JF, Min, Yuan-I, Mitchell, Braxton D, Morrison, Alanna C, Nickerson, Deborah A, North, Kari E, O'Connell, Jeffrey R, Pankratz, Nathan, Psaty, Bruce M, Vasan, Ramachandran S, Rich, Stephen S, Rotter, Jerome I, Smith, Albert V, Smith, Nicholas L, Tang, Hua, Tracy, Russell P, Conomos, Matthew P, Laurie, Cecelia A, Mathias, Rasika A, Li, Yun, Auer, Paul L, NHLBI Trans-Omics For Precision Medicine (TOPMed) Consortium, Thornton, Timothy, Reiner, Alexander P, Johnson, Andrew D, and Raffield, Laura M

Subjects
Blood Platelets, Phenotype, Humans, Precision Medicine, National Heart, Lung, and Blood Institute (U.S.), Polymorphism, Single Nucleotide, United States, 3. Good health, Genome-Wide Association Study
Abstract

Platelets play a key role in thrombosis and hemostasis. Platelet count (PLT) and mean platelet volume (MPV) are highly heritable quantitative traits, with hundreds of genetic signals previously identified, mostly in European ancestry populations. We here utilize whole genome sequencing (WGS) from NHLBI's Trans-Omics for Precision Medicine initiative (TOPMed) in a large multi-ethnic sample to further explore common and rare variation contributing to PLT (n = 61 200) and MPV (n = 23 485). We identified and replicated secondary signals at MPL (rs532784633) and PECAM1 (rs73345162), both more common in African ancestry populations. We also observed rare variation in Mendelian platelet-related disorder genes influencing variation in platelet traits in TOPMed cohorts (not enriched for blood disorders). For example, association of GP9 with lower PLT and higher MPV was partly driven by a pathogenic Bernard-Soulier syndrome variant (rs5030764, p.Asn61Ser), and the signals at TUBB1 and CD36 were partly driven by loss of function variants not annotated as pathogenic in ClinVar (rs199948010 and rs571975065). However, residual signal remained for these gene-based signals after adjusting for lead variants, suggesting that additional variants in Mendelian genes with impacts in general population cohorts remain to be identified. Gene-based signals were also identified at several genome-wide association study identified loci for genes not annotated for Mendelian platelet disorders (PTPRH, TET2, CHEK2), with somatic variation driving the result at TET2. These results highlight the value of WGS in populations of diverse genetic ancestry to identify novel regulatory and coding signals, even for well-studied traits like platelet traits.

20. Sequence data and association statistics from 12,940 type 2 diabetes cases and controls

Author

Flannick, Jason, Fuchsberger, Christian, Mahajan, Anubha, Teslovich, Tanya M, Agarwala, Vineeta, Gaulton, Kyle J, Caulkins, Lizz, Koesterer, Ryan, Ma, Clement, Moutsianas, Loukas, McCarthy, Davis J, Rivas, Manuel A, Perry, John RB, Sim, Xueling, Blackwell, Thomas W, Robertson, Neil R, Rayner, N William, Cingolani, Pablo, Locke, Adam E, Tajes, Juan Fernandez, Highland, Heather M, Dupuis, Josee, Chines, Peter S, Lindgren, Cecilia M, Hartl, Christopher, Jackson, Anne U, Chen, Han, Huyghe, Jeroen R, Van De Bunt, Martijn, Pearson, Richard D, Kumar, Ashish, Müller-Nurasyid, Martina, Grarup, Niels, Stringham, Heather M, Gamazon, Eric R, Lee, Jaehoon, Chen, Yuhui, Scott, Robert A, Below, Jennifer E, Chen, Peng, Huang, Jinyan, Go, Min Jin, Stitzel, Michael L, Pasko, Dorota, Parker, Stephen CJ, Varga, Tibor V, Green, Todd, Beer, Nicola L, Day-Williams, Aaron G, Ferreira, Teresa, Fingerlin, Tasha, Horikoshi, Momoko, Hu, Cheng, Huh, Iksoo, Ikram, Mohammad Kamran, Kim, Bong-Jo, Kim, Yongkang, Kim, Young Jin, Kwon, Min-Seok, Lee, Juyoung, Lee, Selyeong, Lin, Keng-Han, Maxwell, Taylor J, Nagai, Yoshihiko, Wang, Xu, Welch, Ryan P, Yoon, Joon, Zhang, Weihua, Barzilai, Nir, Voight, Benjamin F, Han, Bok-Ghee, Jenkinson, Christopher P, Kuulasmaa, Teemu, Kuusisto, Johanna, Manning, Alisa, Ng, Maggie CY, Palmer, Nicholette D, Balkau, Beverley, Stančáková, Alena, Abboud, Hanna E, Boeing, Heiner, Giedraitis, Vilmantas, Prabhakaran, Dorairaj, Gottesman, Omri, Scott, James, Carey, Jason, Kwan, Phoenix, Grant, George, Smith, Joshua D, Neale, Benjamin M, Purcell, Shaun, Butterworth, Adam S, Howson, Joanna MM, Lee, Heung Man, Lu, Yingchang, Kwak, Soo-Heon, Zhao, Wei, Danesh, John, Lam, Vincent KL, Park, Kyong Soo, Saleheen, Danish, So, Wing Yee, Tam, Claudia HT, Afzal, Uzma, Aguilar, David, Arya, Rector, Aung, Tin, Chan, Edmund, Navarro, Carmen, Cheng, Ching-Yu, Palli, Domenico, Correa, Adolfo, Curran, Joanne E, Rybin, Dennis, Farook, Vidya S, Fowler, Sharon P, Freedman, Barry I, Griswold, Michael, Hale, Daniel Esten, Hicks, Pamela J, Khor, Chiea-Chuen, Kumar, Satish, Lehne, Benjamin, Thuillier, Dorothée, Lim, Wei Yen, Liu, Jianjun, Loh, Marie, Musani, Solomon K, Puppala, Sobha, Scott, William R, Yengo, Loïc, Tan, Sian-Tsung, Taylor, Herman A, Thameem, Farook, Wilson, Gregory, Wong, Tien Yin, Njølstad, Pål Rasmus, Levy, Jonathan C, Mangino, Massimo, Bonnycastle, Lori L, Schwarzmayr, Thomas, Fadista, João, Surdulescu, Gabriela L, Herder, Christian, Groves, Christopher J, Wieland, Thomas, Bork-Jensen, Jette, Brandslund, Ivan, Christensen, Cramer, Koistinen, Heikki A, Doney, Alex SF, Kinnunen, Leena, Esko, Tõnu, Farmer, Andrew J, Hakaste, Liisa, Hodgkiss, Dylan, Kravic, Jasmina, Lyssenko, Valeri, Hollensted, Mette, Jørgensen, Marit E, Jørgensen, Torben, Ladenvall, Claes, Justesen, Johanne Marie, Käräjämäki, Annemari, Kriebel, Jennifer, Rathmann, Wolfgang, Lannfelt, Lars, Lauritzen, Torsten, Narisu, Narisu, Linneberg, Allan, Melander, Olle, Milani, Lili, Neville, Matt, Orho-Melander, Marju, Qi, Lu, Qi, Qibin, Roden, Michael, Rolandsson, Olov, Swift, Amy, Rosengren, Anders H, Stirrups, Kathleen, Wood, Andrew R, Mihailov, Evelin, Blancher, Christine, Carneiro, Mauricio O, Maguire, Jared, Poplin, Ryan, Shakir, Khalid, Fennell, Timothy, DePristo, Mark, De Angelis, Martin Hrabé, Deloukas, Panos, Gjesing, Anette P, Jun, Goo, Nilsson, Peter, Murphy, Jacquelyn, Onofrio, Robert, Thorand, Barbara, Hansen, Torben, Meisinger, Christa, Hu, Frank B, Isomaa, Bo, Karpe, Fredrik, Liang, Liming, Peters, Annette, Huth, Cornelia, O'Rahilly, Stephen P, Palmer, Colin NA, Pedersen, Oluf, Rauramaa, Rainer, Tuomilehto, Jaakko, Salomaa, Veikko, Watanabe, Richard M, Syvänen, Ann-Christine, Bergman, Richard N, Bharadwaj, Dwaipayan, Bottinger, Erwin P, Cho, Yoon Shin, Chandak, Giriraj R, Chan, Juliana Cn, Chia, Kee Seng, Daly, Mark J, Ebrahim, Shah B, Langenberg, Claudia, Elliott, Paul, Jablonski, Kathleen A, Lehman, Donna M, Jia, Weiping, Ma, Ronald CW, Pollin, Toni I, Sandhu, Manjinder, Tandon, Nikhil, Froguel, Philippe, Barroso, Inês, Teo, Yik Ying, Zeggini, Eleftheria, Loos, Ruth JF, Small, Kerrin S, Ried, Janina S, DeFronzo, Ralph A, Grallert, Harald, Glaser, Benjamin, Metspalu, Andres, Wareham, Nicholas J, Walker, Mark, Banks, Eric, Gieger, Christian, Ingelsson, Erik, Im, Hae Kyung, Illig, Thomas, Franks, Paul W, Buck, Gemma, Trakalo, Joseph, Buck, David, Prokopenko, Inga, Mägi, Reedik, Lind, Lars, Farjoun, Yossi, Owen, Katharine R, Gloyn, Anna L, Strauch, Konstantin, Tuomi, Tiinamaija, Kooner, Jaspal Singh, Lee, Jong-Young, Park, Taesung, Donnelly, Peter, Morris, Andrew D, Hattersley, Andrew T, Bowden, Donald W, Collins, Francis S, Atzmon, Gil, Chambers, John C, Spector, Timothy D, Laakso, Markku, Strom, Tim M, Bell, Graeme I, Blangero, John, Duggirala, Ravindranath, Tai, E Shyong, McVean, Gilean, Hanis, Craig L, Wilson, James G, Seielstad, Mark, Frayling, Timothy M, Meigs, James B, Cox, Nancy J, Sladek, Rob, Lander, Eric S, Gabriel, Stacey, Mohlke, Karen L, Meitinger, Thomas, Groop, Leif, Abecasis, Goncalo, Scott, Laura J, Morris, Andrew P, Kang, Hyun Min, Altshuler, David, Burtt, Noël P, Florez, Jose C, Boehnke, Michael, and McCarthy, Mark I

Subjects
Diabetes Mellitus, Type 2, Genetic Variation, Humans, White People, 3. Good health
Abstract

To investigate the genetic basis of type 2 diabetes (T2D) to high resolution, the GoT2D and T2D-GENES consortia catalogued variation from whole-genome sequencing of 2,657 European individuals and exome sequencing of 12,940 individuals of multiple ancestries. Over 27M SNPs, indels, and structural variants were identified, including 99% of low-frequency (minor allele frequency [MAF] 0.1-5%) non-coding variants in the whole-genome sequenced individuals and 99.7% of low-frequency coding variants in the whole-exome sequenced individuals. Each variant was tested for association with T2D in the sequenced individuals, and, to increase power, most were tested in larger numbers of individuals (>80% of low-frequency coding variants in ~82 K Europeans via the exome chip, and ~90% of low-frequency non-coding variants in ~44 K Europeans via genotype imputation). The variants, genotypes, and association statistics from these analyses provide the largest reference to date of human genetic information relevant to T2D, for use in activities such as T2D-focused genotype imputation, functional characterization of variants or genes, and other novel analyses to detect associations between sequence variation and T2D.

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